Search Results - (( parameters detection method algorithm ) OR ( using factorization learning algorithm ))

Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…In addition, the results also showed that the proposed hierarchical classification method could extract geometric road elements with an average error rate of 6.25% for slope parameter and 6.65% for superelevation parameter, and it is transferable to other regions of similar environments. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Application of weighted average on modal parameters for damage detection algorithms: Case study on steel beam by Fayyadh, M.M., Abdul Razak, H.

“…This study verifies the use of the proposed weighting method by Fayyadh and Abdul Razak (2011a) for damage detection algorithms applied on cracked steel beam. …”
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Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…This creates the jamming detection and classification parameters. The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The NTLBO was proposed in this paper as an FSS mechanism; its algorithm-specific, parameter-less concept (which requires no parameter tuning during an optimization) was explored. …”
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Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

“…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Comparison of UAV flying height parameter for crack detection applications / Wan Nurdayini Batrisyia Wan Ghazali by Wan Ghazali, Wan Nurdayini Batrisyia

“…The key concern of this thesis is to determine the influence of flying height parameters on crack detection using UAVs. Looking at the current scenario of development and the age of the structures in urban areas, there is a high significance of efficient and accurate building inspection methods. …”
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Fuzzy modelling using butterfly optimization algorithm for phishing detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail, Nurul Aswa, Omar

“…To generate the fuzzy parameter automatically, an optimization method is required and Butterfly Optimization Algorithm (BOA) is one of the good methods to be applied. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”

Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa'

“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa’

“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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